Modelling Pedestrian Circulation in Rail Transit Stations Using Micro-Simulation

Transcription

1 Modelling Pedestrian Circulation in Rail Transit Stations Using Micro-Simulation ATRF 2009 Venue: Auckland, New Zealand Date: September 30, 2009 Galiza*/Kim**/Ferreira*/Laufer** *University of Queensland **PTV-Asia Pacific 1

2 Introduction Increased public transport use (bus & rail) Photo courtesy of ITSRR-NSW Increased congestion esp. during peak periods Photo courtesy of ITSRR-NSW 2

3 Problem Statement Traditional design & evaluation of pedestrian facilities maintaining a desirable pedestrian level-of-service (PLOS) Walkway Levels of Service (Fruin 1987) 3

4 Issues on Pedestrian Analysis Cultural differences Traveller composition/distribution Type of facilities & environment factors Designing pedestrian facilities complying with local characteristics? 4

5 Micro-simulation Traffic models (MSTMs) widely accepted tools guidelines available (FHWA 2004; Austroads 2006; Faber Maunsell 2007). 5

6 Why not also use micro-simulation for pedestrian analysis? Micro-simulation pedestrian software (e.g. VISSIM, SimWalk, Legion, NoMad ) 6

7 Conventional Pedestrian Circulation Analysis Use of link-node network & spreadsheets 7

8 Advantages of Pedestrian Micro-simulation Flexible geometric irregularities Non-uniform passenger arrivals Greater number of influencing factors Visual pedestrian interactions 8

9 Disadvantages of Micro-simulation Time-consuming & expensive Considerable input data Extensive calibration, validation & verification Micro-simulation as black boxes 9

10 Data Collection Sufficient time & resources input data collection Static data - scaled station plans, locations of temporary equipment, trash bins, obstructions, & ticket vending machines. Dynamic data - train arrivals, pedestrian volumes & characteristics. 10

11 Modelling Criteria No modelling criteria - MSPM calibration MSTM criteria applied percent deviation (observed - modelled volumes) or GEH statistics - pedestrian volumes GEH = 2 ( M O) M + O 2 11

12 Possible Scenarios (Station analysis) Rolling stock changes Additional services Service delay impacts Passenger volumes changes Platform arrival changes Passenger evacuation 12

13 VISSIM Pedestrian Simulation Vehicles & pedestrians simulated individually Pedestrian behaviour defined individually Area based modelling Multiple level representation Pedestrian dynamic route choice Forces from fellow pedestrians Forces from borders Driving force in the desired direction of motion 13

14 North Melbourne Station (NMS): Case Study located north of Melbourne CBD contains six platforms four ramps - northern end 3 platforms for NB & SB 14

15 Base Model Operational Characteristics Rail Frequency for the AM Peak Period (Laufer 2008) Platform Number Total No. of Services (Trains) Simulated during AM peak hour (7:30 8:30AM) Services current timetable May 2008 Patronage October 2007 receives ~3,000 persons alighting 40% exit &60% transfer 15

16 Base Model Network Coding platforms & concourses - pedestrian areas connections between levels - ramps shelters, poles & other furniture - obstacles 16

17 Base Model Calibration Good network depiction 17

18 Base Model Calibration Platform Simulation Volumes (Laufer 2008) Absolute Percentage Observed Modelled Pedestrian Movement Difference Difference Platform 1 Entering % Platform 1 Leaving % Platform 2 & 3 Entering % Platform 2 & 3 Leaving % Platform 4 & 5 Entering % Platform 4 & 5 Leaving 1, % Total 3, % 18

19 Model Performance Measures Platform Occupancy in the SB Direction (Laufer 2008) 19

20 Model Performance Measures Platform 1 Pedestrian Level-of-service from Fruin (1971) 20

21 Lessons Learned Illustrated how the NMS can be modelled using pedestrian microsimulation. Identified procedure & data requirements Produces broad number of quantitative outputs. Visualization for qualitative congestion measure. 21

22 Lessons Learned Requires considerable data and manpower. More expensive than traditional analysis. Capital investment on software. No agreed upon calibration guidelines. 22

23 Conclusions and Future Research Simulation - powerful tool for passenger flow analysis. Provides numerical results & graphical animations. Investigate pedestrian characteristics for Australian conditions. Establish guidelines for MSPM use. 23

24 Thank you for listening, that ends the presentation Your questions, comments & suggestions are most welcome 24